The Disabled Researcher: Research Design That Makes Room for Real Life

Starting from the inside

My PhD thesis explored how students with acquired brain injuries navigate online higher education. I am also a member of that community.

At the time, my cognitive black holes, unreliable memory, screen-induced migraines, and fatigue were not separate from the research process. They affected how long I could work, how I processed information, and what I needed in order to keep going.

That did not make rigorous research impossible. It meant I had to design research that was rigorous in the real conditions where it was being done.

I used a reflective, remote autoethnographic approach, informed by critical disability theory and reflexive thematic analysis (Bamkin et al., 2016; Savage, 2000; McRuer, 2006; Hanebutt & Mueller, 2021; Braun & Clarke, 2022).

Put more plainly, I needed a method that made room for my own experience while still treating participants’ accounts with care and structure.

The theory behind the choices

The social model of disability was one starting point. It distinguishes between impairment and disability (Berghs et al., 2016; Retief & Letšosa, 2018; Purtell, 2013). An impairment may affect how someone’s body or brain functions. Disability is also created by barriers, such as inaccessible software, inflexible deadlines, or a learning environment that assumes everyone can process information in the same way.

That was useful, but it did not fully capture the messy reality of living with an acquired brain injury. I also drew on Crip theory, which treats disability as part of identity rather than a medical deficit that needs to be corrected (McRuer, 2006; Hanebutt & Mueller, 2021).

Central to this was the idea of crip tax: the extra cognitive, physical, financial, and temporal labour disabled people may have to expend simply to participate (Blanchard, 2020; Katzman et al., 2024). In my case, that could mean spending three hours reading one journal article, losing days to screen-induced migraines, or having to reorganize work around fluctuating symptoms.

I also had to account for crip time (Blanchard, 2020): the recognition that time and capacity do not always move in predictable or linear ways. Schedules are not always tidy when symptoms flare, seizures happen, cognitive fatigue hits, or a task simply takes longer than the plan said it should.

A framework for trust

I developed four guiding commitments for data collection: inclusion, flexibility in design, meeting participants where they were at, and building trust through up-front disclosure.

Disabled people are often researched on rather than researched with (Dolmage, 2017; Lester & Nusbaum, 2018; Mertens, 2015). The disability-rights principle “nothing about us without us” was one reason I wanted to co-construct knowledge with participants instead (Charlton, 1998; Noel, 2016; Hofmann et al., 2020).

That began with disclosure. I included a letter in the recruitment materials that explained my own injury history and some of the communication barriers we might encounter. If I struggled to find a word, needed to wear tinted glasses in a video meeting, or took longer to process what someone had said, participants knew what was happening.

I was not trying to perform expertise from behind a glass partition. I was simply there alongside them.

That honesty helped level the power relationship. It made room for a partnership based on shared expertise rather than a traditional arrangement in which the researcher holds most of the authority.

The remote research toolkit

I chose remote ethnography partly because it allowed me to work with participants across Canada, the UK, the USA, and Australia. Remote ethnography can reduce the need for physical proximity and travel, which can be particularly important when participants and researchers have access, health, or safety considerations (Bengtsson, 2014; Postill, 2016).

Over eight months, I worked with eight other online students with acquired brain injuries. Together with my own autoethnographic material, the study included nine participants. Participants ranged from undergraduate to PhD level.

Data collection took place in three phases:

• Surveys: Participants completed the Rivermead Post-Concussion Symptom Questionnaire and a symptom self-evaluation questionnaire, which I used to establish a baseline of cognitive, emotional, physical, and sleep-related symptoms.
• Semi-structured interviews: We met through virtual meeting software, with captioning or transcription enabled to reduce some of the audio-processing barriers we shared.
• Ethnographic artefacts: Participants could choose written, audio, or video journaling. Six participants submitted journal artefacts, and all six chose written documents. Some also included visual materials related to their learning environments or tools.

Accessibility is not about guessing one best format for everyone. It is about making meaningful options available, then respecting what people choose. This reflects the principle of meeting people where they are at, emotionally, mentally, physically, and practically (National Health Corps, 2021).

Making transcripts useful

Transcription was useful, but it was not automatic accessibility. AI-generated transcripts often contained errors, especially where speech patterns, accents, or word choices did not fit what the software expected.

I manually checked interview recordings against the initial transcripts before asking participants to review them. Participants could correct errors, add comments, expand on something they had said, or remove material they no longer wanted included.

My analysis was iterative rather than linear. After each round of interviews, I reviewed and coded the material, used emerging patterns to refine later questions, and returned to earlier transcripts to check whether I had interpreted similar experiences consistently.

The manual and digital anchor

My analysis followed Braun and Clarke’s (2022) six-phase approach to reflexive thematic analysis. The practical work of analysis, though, was shaped by ABI.

Digital repositories and new software could be a constant source of frustration because the process did not always stick in my memory. I returned to what worked. I used printed transcripts, handwritten notes, coloured pens, and conceptual memos in the margins to begin coding.

I used Microsoft Excel to manage the data because I had worked with it for more than 25 years. It was familiar. It gave me a stable place to organize codes related to systemic barriers, instructor impact, and the strategies participants used to keep learning.

Familiarity was an accessibility feature. I did not need the most sophisticated tool available. I needed one I could use reliably when cognitive capacity was limited.

Once again, past me supported current me.

Grace in the method

My research journal began as occupational therapy, but it also became a primary data source. It held my notes about trying to differentiate old me from new me, and about the humility required when a task I thought would take weeks took four months instead.

I designed the methodology to be accessible, including by limiting academic jargon where I could. This was a practical design choice: I wanted the resulting text to remain useful to readers with acquired brain injuries and other non-specialist audiences, rather than placing an additional cognitive burden on them.

I have learned that even when memory is unreliable, the stories we gather still matter. Collected with patience and grace, they can show us what needs to change.